Evidence map›Paper›PMID 31216675›Full record

ReviewMetabolites2019

Integration of Metabolomic and Other Omics Data in Population-Based Study Designs: An Epidemiological Perspective.

Su H Chu, Mengna Huang, Rachel S Kelly, Elisa Benedetti, Jalal K Siddiqui, Oana A Zeleznik, Alexandre Pereira, David Herrington, Craig E Wheelock, Jan Krumsiek and 6 more

Abstract readReview
In one paragraph

Review in Metabolites, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Observational
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Ovarian Cancer: Multi-Omics Data Integration.International journal of molecular sciences · 2025
    Review
  10. Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. An epidemiological introduction to human metabolomic investigations.Trends in endocrinology and metabolism: TEM · 2023
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Su H ChuChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. su.chu@channing.harvard.edu.ORCID 0000-0002-6345-008X
Mengna HuangChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. mengna.huang@channing.harvard.edu.
Rachel S KellyChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. hprke@channing.harvard.edu.ORCID 0000-0003-3023-1822
Elisa BenedettiInstitute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10021, USA. elb4003@med.cornell.edu.
Jalal K SiddiquiDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA. jalal.siddiqui@osumc.edu.ORCID 0000-0002-5100-6432
Oana A ZeleznikChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. ozeleznik@bwh.harvard.edu.
Alexandre PereiraDepartment of Genetics and Molecular Medicine, University of Sao Paulo Medical School, Sao Paulo 01246-903, Brazil. alexandre.pereira@incor.usp.br.
David HerringtonDepartment of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA. dherring@wakehealth.edu.
Craig E WheelockDivision of Physiological Chemistry 2, Department of Medical Biochemistry and Biophysics, Karolinska Institute, 171 77 Stockholm, Sweden. craig.wheelock@ki.se.ORCID 0000-0002-8113-0653
Jan KrumsiekInstitute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10021, USA. jak2043@med.cornell.edu.ORCID 0000-0003-4734-3791
Michael McGeachieChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. remmg@channing.harvard.edu.
Steven C MooreDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA. Steve.Moore@nih.gov.
Peter KraftDepartment of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA. pkraft@hsph.harvard.edu.
Ewy MathéDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA. ewy.mathe@osumc.edu.ORCID 0000-0003-4491-8107
Jessica Lasky-SuChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. jessica.su@channing.harvard.edu.
Consortium of Metabolomics Studies Statistics Working Group

Funding

Physical Activity, Energy Balance, and CancerZIACP010197 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ALBANES, DEMETRIUS · 2009 to 2025
$17.5M
Genomic and Proteomic Architecture of AtherosclerosisR01HL111362 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI HERRINGTON, DAVID MCLEOD · 2012 to 2021
$17.2M
Finding Genomic Profiles of COVID-19 Phenotypes from the EHRU01HG008685 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIZABETH W KARLSON, Matthew S Lebo · 2015 to 2026
$13.6M
Systems Biology of Airway DiseaseP01HL132825 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI WEISS, SCOTT T · 2016 to 2020
$12.6M
Novel Biomarkers and Prediction Models for Rheumatoid ArthritisR01AR049880 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI COSTENBADER, KAREN H, KARLSON, ELIZABETH W · 2003 to 2018
$8.7M
Integrative Metabolomics of Asthma SeverityR01HL123915 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LASKY-SU, JESSICA A · 2014 to 2023
$7.0M
Asthma Exacerbations and MicroRNA prediction: Treatment Response in an Underserved Ethnicity (AEM-TRUE)R01HL139634 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI MCGEACHIE, MICHAEL JOHN · 2018 to 2022
$4.3M
Mechanistic insights into asthma pathogenesis through the integration of asthma genes, risk exposures, and metabolomicsR01HL141826 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LASKY-SU, JESSICA A · 2018 to 2021
$3.4M
Metabolomic Signatures of CAD Associated GenotypesR01HL133932 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI BOWDEN, DONALD W, HERRINGTON, DAVID MCLEOD · 2016 to 2019
$2.5M
Multi-Omic Endotyping of AsthmaK01HL146980 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI KELLY, RACHEL SABINE · 2019 to 2023
$891k
NHGRI NIH HHS U01 HG008685-01NHLBI NIH HHS K01 HL146980NHLBI NIH HHS K01HL146980NHLBI NIH HHS P01 HL132825NHLBI NIH HHS R01 HL111362NHLBI NIH HHS R01 HL123915NHLBI NIH HHS R01HL123915NHLBI NIH HHS R01 HL133932NHLBI NIH HHS R01HL133932NHLBI NIH HHS R01 HL139634NHLBI NIH HHS R01 HL141826NHLBI NIH HHS R01HL141826NIAMS NIH HHS R01AR049880
6 · The paper itself

Abstract

It is not controversial that study design considerations and challenges must be addressed when investigating the linkage between single omic measurements and human phenotypes. It follows that such considerations are just as critical, if not more so, in the context of multi-omic studies. In this review, we discuss (1) epidemiologic principles of study design, including selection of biospecimen source(s) and the implications of the timing of sample collection, in the context of a multi-omic investigation, and (2) the strengths and limitations of various techniques of data integration across multi-omic data types that may arise in population-based studies utilizing metabolomic data.

Indexed as

epidemiologyintegrative analysismulti-omic integrationstudy designsystems biology

Identifiers

PMID31216675
PMCPMC6630728

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.